A successful candidate to this course learns a series of best practices forthe development of efficient parallel codes, capable to exploit a distributed multi-core platform for HPC, equipped with add-on accelerators, including being able to effectively analyze the performance of parallel code.
She/he will be able to analyze the main computational aspects of a given problem, implementing scalable and efficient strategies of parallelization.
GPU and Parallel Programming
Learning Goals
Program in pills
Best practices of efficient parallel and GPU programming for HPC. Advanced programming for modern high-end systems for HPC.
Performance analysis of parallel applications.
Area
Computer Science and Intensive Computing
Curriculum Foundations
TAF Type
Curriculum Industry
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Curriculum Health
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Curriculum Economy
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SSD
ECTS
Semester
Lecturers